Full Motion and Flow Field Recovery from Echo Doppler Data

We present a new computational method for reconstructing a vector velocity field from scattered, pulsed-wave ultrasound Doppler data. The main difficulty is that the Doppler measurements are incomplete, for they do only capture the velocity component along the beam direction. We thus propose to combine measurements from different beam directions. However, this is not yet sufficient to make the problem well posed because 1) the angle between the directions is typically small and 2) the data is noisy and nonuniformly sampled. We propose to solve this reconstruction problem in the continuous domain using regularization. The reconstruction is formulated as the minimizer of a cost that is a weighted sum of two terms: 1) the sum of squared difference between the Doppler data and the projected velocities 2) a quadratic regularization functional that imposes some smoothness on the velocity field. We express our solution for this minimization problem in a B-spline basis, obtaining a sparse system of equations that can be solved efficiently. Using synthetic phantom data, we demonstrate the significance of tuning the regularization according to the a priori knowledge about the physical property of the motion. Next, we validate our method using real phantom data for which the ground truth is known. We then present reconstruction results obtained from clinical data that originate from 1) blood flow in carotid bifurcation and 2) cardiac wall motion

BIMODAL MYOCARDIAL MOTION ANALYSIS FROM B-MODE AND TISSUE DOPPLER ULTRASOUND

ABSTRACT We present a new method for estimating heart motion from two-dimensional echocardiographic sequences by exploiting two ultrasound modalities: B-mode and tissue Doppler. The algorithm estimates a two-dimensional velocity field locally by using a spatial affine velocity model inside a sliding window. Within each window, we minimize a local cost function that is composed of two quadratic terms: an optical flow constraint that involves the B-mode data and a constraint that enforces the agreement of the velocity field with the directional tissue Doppler measurements. The relative influence of the two different modalities to the resulting solution is controlled by an adjustable weighting parameter. Robustness is achieved by a coarse-to-fine multi-scale approach. The method was tested on synthetic ultrasound data and validated by a rotating phantom experiment. First applications to clinical echocardiograms give promising results

Bimodal Myocardial Motion Analysis from B-Mode and Tissue Doppler Ultrasound

We present a new method for estimating heart motion from two-dimensional echocardiographic sequences by exploiting two ultrasound modalities: B-mode and tissue Doppler. The algorithmestimates a two-dimensional velocity field locally by using a spatial affine velocity model inside a sliding window. Within each window, we minimize a local cost function that is composed of two quadratic terms: an optical flow constraint that involves the B-mode data and a constraint that enforces the agreement of the velocity field with the directional tissue Doppler measurements. The relative influence of the two differentmodalities to the resulting solution is controlled by an adjustable weighting parameter. Robustness is achieved by a coarse-to-fine multi-scale approach. The method was tested on synthetic ultrasound data and validated by a rotating phantom experiment. First applications to clinical echocardiograms give promising results

Automated speckle tracking in ultrasound images of tendon movements

The central aim of this thesis was to develop new tracking software employing various image tracking algorithms for tracking the speckled movement of the tendon image captured using dynamic B-mode ultrasound imaging. The algorithms were selected based on the literature related to the tracking of images captured using ultrasound imaging. Experiments were carried out to validate these tracking algorithms in order to enable development of the tracking software. The experiments conducted paralleled the objectives in designing, developing, experimenting and implementing the image-tracking algorithm to track movement of the human tendon in vivo within the speckled ultrasound images. The development of the tracking software focuses on solving the problems of tracking the ultrasound images as well as analysing the tracking movement frame-by-frame to produce useful measurements that can be used to describe the localised mechanical and structural properties of the human tendon.The algorithms tested were Normalised Cross Correlation (NCC), Mean Square Error (MSE), optical flow – Lucas-Kanade (LK) and combination of NCC and MSE (NCCMSE) selected by signal-to-noise ratio (SNR) and were tested on both active and passive movements of the patella tendon (knee) and the medial gastrocnemius tendon (ankle). The comparison of the algorithms led to the identification of a single algorithm giving optimal result. The results from all tested algorithm showed NCC to be the closest match to the standard manual measurement. NCC was also the fastest among the algorithms tested and contained fewer errors in tracking.For NCC algorithm, various sizes of the region of interest (ROI) block were also tested and found that 15x15 pixels ROI block size gave the optimum measurement, which was close to the standard manual measurement. The threshold levels also indicated that >0.90 to be the optimum level for optimum tracking. The 2- ROI tracking analysis were also explored to look at the tracking performances when tracking at two different regional sites of the tendon simultaneously, and again theNCC performed better with 15x15 ROI block size and comparable to the results obtained from the standard manual measurement.Lastly, multiple layers of the tendon were also explored to look at the excursion of the anterior, midsection and posterior layers of the tendon during ramped isometric contraction. This experiment uses all the settings found from previous experiment results, and applied to look at the mechanical properties of the human tendon. The experiments showed that the anterior gave the highest mean stain followed by the mid section and the smallest mean strain was found at the posterior proximal. The experiment also looked at the distal strain, with the result showing that the posterior gave the highest mean strain followed mid section and anterior layer gave the smallest mean strain. The experiment also looked at the performance of posterior layers and distal layers at 50 and 100% force levels.The experimental results showed that the NCC to be the optimum-tracking algorithm. The method described here has the potential to improve clinical knowledge relating to the tendon mechanical properties. The information generated by the tracking algorithm could help to give further insight into the aetiology of tendon injury, repair, response to various training interventions and the time course of tissue adaptation with disease